Properly implemented, AI is the biggest economic opportunity for businesses of any size around the world in the next decade. AI has received much media attention. Subsequently many organizations are beginning to engage in the process of simply understanding what AI has to offer their business.
However, as outlined in a report by BCG and MIT Sloan Management Review, enterprises identity the following three factors that lead to an organization's slow adoption of AI:
Integration of AI related products and services is becoming more important if not vital to the future success of an organization. At Accelerated InSite we understand the current market maturity and the future exponential growth of AI advances. As a result, our AI Consulting Services are designed to build a "lean approach" that enables an organization to effectively and efficiently overcome the three factors that drive slow adoption.
Relying on specialists in human centered design and systemic thinking, project management, process improvement, organizational training, and technology applications, our assessment teams are constituted to achieve your objectives on your terms.
First, as part of an assessment of your organization's readiness for AI we identify what "gaps" need to be filled over time from most to least critical.
Within the organizational assessment we also identify specific business issues which have low complexity and high benefit and use those as AI case studies to raise awareness within your organization as AI capabilities. See Prioritization Assessment Matrix here Insuring success of these initial projects increases confidence in the value of AI and provides a pathway forward for additional AI projects.
The final segment of the organizational assessment is to identify the depth and breadth of your human capital capabilities relevant to both the skills and knowledge inventory. Therefore, a training and education plan can be established with the aim of internalizing the needed capacity to further optimize the power of AI unique to your business in the long term.
Our approach provides a short term AI strategy which allows for increased awareness of the capabilities of AI. Short term wins through basic training begins the process. As a result, more informed focus can be spent creating a three year strategy, mapping out more projects and defining integrated training and awareness efforts that involve all stakeholders.
Avoiding "one size fits all" deliverables, there are different variations of this approach that can be designed for any organization depending on its size and the outcomes of the initial assessment.
If there are any questions concerning how we would design our services around your needs please feel free to arrange an appointment.
Accelerate InSite works with customers to determine what the problem to be solved or the work to be done consists of. We take a staged approach defined by the customer's needs as outlined in our assessment roadmap.
Accelerate InSite provides three primary services aimed at helping organizations assess, plan and implement artificial intelligence applications into their operations. Evidence suggests, and we believe, that unless AI is applied systemically from an organizational point of view, potential outcomes will be limited. Our services are focused in three areas: Consulting, Technology and Education.
AI and Machine Learning are powerful tools that can be deployed for the provisioning of leading-edge services and products that will set your organization apart from your competition. Some examples in which AI has been applied successfully include:
1. Automated Customer Support
2. Enhanced Online Shopping Experiences
3. Healthcare industry delivery, pricing, collections and quality of medical care
4. Financial Industry real-time reporting, accuracy, and processing of large volumes of quantitative data to make crucial decisions
5. Automated document management and production
6. Process automation across any industry
And the list grows significantly every day with more and more discoveries of how AI can be applied to solve real problems by leveraging innovative solutions using AI.
Below is some further categorization of AI usage.
Cognitive Customer Care
Customers of today expect fast, accurate and interactive services for real time communication. A virtual AI assistant can be designed to improve your customer experience by reducing operation cost through an AI Chat bot or a Virtual Interactive Agent based on the Industry you serve.
Enhance value to your business heuristics with a prediction solution that effectively identifies your specific risk before it metastasizes into a disaster. Through a custom designed predictive analytic tool, an improved data management process can be customized around your risk criteria. Custom built AI engines can furnish end-to-end risk and compliance management for better decisions as well as risk management related assessments.
Object and Image Detection
Based on your industry, object detection trains AI models to reduce the consumption of time and cost through detecting objects of interest or concern contained in digital data. From facial to voice recognition, object detection improves the accuracy of locating essential images in unstructured data. Raw detection as well as the rich set of statistical analytics are provided by deep learning systems through visibility analysis and automated object detection.
Leveraging the power of Natural Language Processing (NLP) AI can scrutinize the sentiment of text and sort it as positive, negative or neutral. This can yield up to 50% better outcomes than rules-based systems to detect emotional content of digital messages as it cuts down false alarms. This AI application improves relationship maintenance with your customers, employees and vendors.
AI intent analysis in Chat bots can recognize the body text when your customer types the message. This service will also understand your customer's need. AI can deliver the right intent based on your industry, for a better response among your customers.
Accelerate InSite has engineers and developers who can build an AI application to do whatever creates the most value for you and your stakeholders.
Accelerate InSite has engineers and developers that can build an AI application to do what you can't even imagine.
We use a combination of the latest technologies to develop outstanding AI applications.
We are developing a full curriculum of online courses covering the essentials of AI and ML. Our initial list consists of free offerings currently made available through some of the market's top suppliers. As our own curriculum and those of our partnerships develop we will announce additional courses through our newsletter. Please be sure to subscribe so we can keep you up to date. Our aim is to keep you equipped with the best knowledge available . Click on the images to view the course.
The course covers the ground from a basic introduction to machine learning, to getting started with TensorFlow, to designing and training neural nets.
It is designed so that those with no prior knowledge of machine learning can jump in right at the start, those with some experience can pick or choose modules which interest them, while machine learning experts can use it as an introduction to TensorFlow.
This is a slightly more in-depth course from Google offered through Udacity. As such, it isn’t aimed at complete novices and assumes some previous experience of machine learning, to the point where you are at least familiar with supervised learning methods.
It focuses on deep learning, and the design of self-teaching systems that can learn from large, complex datasets.
The course is aimed at those looking to put machine learning, neural network technology to work as data analysts, data scientists or machine learning engineers as well as enterprising individuals wanting to make use of the plethora of open source libraries and materials available.
This course is offered through Coursera and is taught by Andrew Ng, the founder of Google’s deep learning research unit, Google Brain, and head of AI for Baidu.
The entire course can be studied for free, although there is also the option of paying for certification which could certainly be useful if you plan to use your understanding of AI to increase your career prospects.
The course covers the spectrum of real-world machine learning implementations from speech recognition and enhancing web search, while going into technical depth with statistics topics such as linear regression, the backpropagation methods through which neural networks “learn”, and a Matlab tutorial – one of the most widely used programming languages for probability-based AI tools.
Machine Learning is the basis for the most exciting careers in data analysis today. You’ll learn the models and methods and apply them to real world situations ranging from identifying trending news topics, to building recommendation engines, ranking sports teams and plotting the path of movie zombies.
Major perspectives covered include:
In the first half of the course we will cover supervised learning techniques for regression and classification. In this framework, we possess an output or response that we wish to predict based on a set of inputs. We will discuss several fundamental methods for performing this task and algorithms for their optimization.
In the second half of the course we shift to unsupervised learning techniques. In these problems the end goal less clear-cut than predicting an output based on a corresponding input. We will cover three fundamental problems of unsupervised learning: data clustering, matrix factorization, and sequential models for order-dependent data. Some applications of these models include object recommendation and topic modeling.
Computer vision is the AI sub-discipline of building computers which can “see” by processing visual information in the same way our brains do.
As well as the technical fundamentals, it covers how to identify situations or problems which can benefit from the application of machines capable of object recognition and image classification.
As a manufacturer of graphics processing units (GPUs), Nvidia unsurprisingly covers the crucial part these high-powered graphical engines, previously primarily aimed at displaying leading-edge images, has played in the widespread emergence of computer vision applications.
The final assessment covers building and deploying a neural net application, and while the entire course can be studied at your own pace, you should expect to spend around eight hours on the material.
These initial offering are provided by third parties and are free for use.